Abstract
We study the effect of noise on a nonlinear neurodynamical model for disease states of recurrent affective disorders. Specifically, we consider how noise affects a model state with periodic event generation close to period-doubling bifurcations. Our simulations demonstrate noisy precursors of the bifurcations. The precursors can be seen in the return maps of the time series and can be quantified with a recently developed algorithm for the detection of unstable periodic orbits. Implications for the neurobiology and course of mood disorders are discussed.
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